Jordan Kesshi, Morin Olivier, Wahl Michael, Amirbekian Bagrat, Chapman Christopher, Owen Julia, Mukherjee Pratik, Braunstein Steve, Henry Roland
Department of Neurology, University of California, San Francisco, San Francisco, CA, United States.
Joint Graduate Group in Bioengineering, University of California San Francisco and University of California Berkeley, San Francisco/Berkeley, CA, United States.
Front Oncol. 2019 Aug 30;9:810. doi: 10.3389/fonc.2019.00810. eCollection 2019.
There is evidence from histopathological studies that glioma tumor cells migrate preferentially along large white matter bundles. If the peritumoral white matter structures can be used to predict the likely trajectory of migrating tumor cells outside of the surgical margin, then this information could be used to inform the delineation of radiation therapy (RT) targets. In theory, an anisotropic expansion that takes large white matter bundle anatomy into account may maximize the chances of treating migrating cancer cells and minimize the amount of brain tissue exposed to high doses of ionizing radiation. Diffusion-weighted MRI (DW-MRI) can be used in combination with fiber tracking algorithms to model the trajectory of large white matter pathways using the direction and magnitude of water movement in tissue. The method presented here is a tool for translating a DW-MRI fiber tracking (tractography) dataset into a white matter path length (WMPL) map that assigns each voxel the shortest distance along a streamline back to a specified region of interest (ROI). We present an open-source WMPL tool, implemented in the package Diffusion Imaging in Python (DIPY), and code to convert the resulting WMPL map to anisotropic contours for RT in a commercial treatment planning system. This proof-of-concept lays the groundwork for future studies to evaluate the clinical value of incorporating tractography modeling into treatment planning.
组织病理学研究表明，胶质瘤肿瘤细胞优先沿大的白质束迁移。如果肿瘤周围白质结构可用于预测手术切缘外肿瘤细胞迁移的可能轨迹，那么该信息可用于指导放射治疗（RT）靶区的划定。理论上，考虑大的白质束解剖结构的各向异性扩展可能会最大化治疗迁移癌细胞的机会，并最小化暴露于高剂量电离辐射的脑组织量。扩散加权磁共振成像（DW-MRI）可与纤维追踪算法结合使用，利用组织中水分子运动的方向和大小来模拟大的白质通路的轨迹。本文介绍的方法是一种将DW-MRI纤维追踪（tractography）数据集转换为白质路径长度（WMPL）图的工具，该图为每个体素分配沿流线回到指定感兴趣区域（ROI）的最短距离。我们展示了一个开源的WMPL工具，它是在Python中的扩散成像包（DIPY）中实现的，以及将生成的WMPL图转换为商业治疗计划系统中用于RT的各向异性轮廓的代码。这一概念验证为未来评估将纤维追踪建模纳入治疗计划的临床价值的研究奠定了基础。
